Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false; the description adds non-obvious operational context beyond them, namely 'Free; no credits debited', which matters given the sibling buy_credits. It doesn't discuss failure modes for invalid distribution types, but the output schema covers return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences plus a compact JSON example, with the purpose front-loaded before the usage condition and the cost note. The example slightly restates what the schema already documents, keeping it just short of maximally efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a full schema, complete annotations, and an output schema, the description covers purpose, cost, and a canonical invocation example. It leaves the mapping from distribution_type to which estimate fields are required to the schema, which is acceptable given the schema's per-field descriptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the worked example adds meaning by showing how distribution_type, min_estimate, max_estimate, and percentile_range combine into one coherent call. It also verbally maps 'most-likely value' to mode_estimate, clarifying an otherwise ambiguous field name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Converts') and a specific resource ('a human-style estimate ... into the distribution_params a root node needs'), which is a transformation distinct from siblings like estimate or run_simulation. The example input makes the scope unambiguous without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states the trigger condition: 'Use this when you have a rough verbal estimate like "between 80 and 120, 90% confident" and need engine-ready parameters rather than guessing them yourself.' That is clear positive guidance, but no when-not-to-use or explicit alternative sibling is named (e.g. when to prefer estimate or run_simulation instead).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.